Introduction
The core message of this manuscripts are as follows:
- Resource use differs between H. curtus and H. schistosus
- Variation in fishing intensity of trawlers and gillnets affects patterns of resource use
This file was last update on 2020-05-23
Varition in fishing intensity along the sindhudurg coast
Calculating effort with depth
Fishing intensity: Vessel effort = Number of days fishing x No. of hauls x Average time per haul is calculated for each boat on each day. This is then totaled for the sampling duration at each site.
- Should fishing intensity be analysed seperately by fishing gear.
- Should calculation of fishing intensity factor in Gears.
dep_int = effort%>%
filter(Fishing.Location != "")%>% #removing missing location data
dplyr::select(Date, Gear.Type, Fishing.Location, Boat.name,
No..of.Hauls, Average.Haul.Time..Hours., No..of.Days.fishing, Depth..wav.)%>%
group_by(Gear.Type)%>%
mutate(n.days = ifelse(is.na(No..of.Days.fishing), #filling in missing data with means
median(No..of.Days.fishing, na.rm = T), No..of.Days.fishing),
n.hauls = ifelse(is.na(No..of.Hauls),
mean(No..of.Hauls, na.rm = T), No..of.Hauls),
haul.time = ifelse(is.na(Average.Haul.Time..Hours.),
mean(Average.Haul.Time..Hours., na.rm = T), Average.Haul.Time..Hours.))%>%
ungroup()%>%
mutate(effort =
(n.days)*(n.hauls)*(haul.time),
Depth.m = Depth..wav.*1.87)%>%
dplyr::select(Date, Boat.name, Gear.Type, Fishing.Location, Depth.m, effort)%>%
drop_na()
Variable type: numeric
| effort |
GillNet |
0 |
1 |
1.12 |
0.67 |
0.17 |
0.75 |
1.00 |
1 |
4 |
▅▇▂▁▁ |
| effort |
Trawler |
0 |
1 |
17.33 |
7.92 |
4.00 |
12.00 |
17.38 |
18 |
48 |
▅▇▂▁▁ |
| -16.20868 |
1.120948 |
17.32963 |
-21.11231 |
0 |
## [1] 3.235314
Mapping fishing intensity
How do we use location and depth data gathered from fisher surveys to map fishing intensity?
- Nearest landmarks are geocoded from google maps API
- Latitude is extracted from landmark geocode
- Match landmark latitude and depth from survey to GEBCO data
- Extract final longitude from GEBCO data

Are points accurately depicted?
Survey based map of fishing intensity needs to be verified with onboard observations and/or remote GPS data.
DIfference in distribution and habitat use between H. curtus and H. shcistosus
Mapping sea snake distribution with fisheries survey data
#Calculating sea snake abundance
snakes_den = snakes%>%
filter(Species == "Hydrophis schistosus" | Species == "Hydrophis curtus",
Fishing.Location != "",
!is.na(Depth.Caught..m.))%>%
dplyr::select(Species, Fishing.Location, Depth.Caught..m., Date, Boat.Name.Owner,
No..of.Hauls, Average.Haul.Duration..Hours., Gear.Type)%>%
group_by(Gear.Type)%>%
mutate(n.hauls = ifelse(is.na(No..of.Hauls),
median(No..of.Hauls, na.rm = T), No..of.Hauls),
haul.time = ifelse(is.na(Average.Haul.Duration..Hours.),
median(Average.Haul.Duration..Hours., na.rm = T),
Average.Haul.Duration..Hours.))%>%
group_by(Date, Boat.Name.Owner)%>%
summarise(HC = sum(Species == "Hydrophis curtus"),
HS = sum(Species == "Hydrophis schistosus"),
effort = last(n.hauls*haul.time),
Fishing.Location = last(Fishing.Location),
Depth.Caught..m. = last(Depth.Caught..m.))%>%
gather(c("HC", "HS"), value = n, key = "Species")%>%
mutate(CPUE = n/effort)%>%
drop_na()
| GillNet |
396 |
541.12 |
| Rampan |
60 |
214.90 |
| Trawler |
40 |
185.50 |
Data summary
| Name |
Piped data |
| Number of rows |
228 |
| Number of columns |
4 |
| _______________________ |
|
| Column type frequency: |
|
| numeric |
2 |
| ________________________ |
|
| Group variables |
None |
Variable type: numeric
| HC |
0 |
1 |
0.38 |
1.90 |
0 |
0 |
0 |
0 |
14.84 |
▇▁▁▁▁ |
| HS |
0 |
1 |
1.32 |
7.32 |
0 |
0 |
0 |
0 |
94.98 |
▇▁▁▁▁ |

- Why does the join reduce from 101 -> 92
- Why is H. curtus only found around and off Malvan?
Do H. schistosus and H.curtus partition the coastal habitat along the depth axis?
Summarising depth use by species
Variable type: numeric
| mean.depth |
HC |
0 |
1 |
-29.59 |
10.9 |
-47.48 |
-38.93 |
-28.36 |
-21.05 |
-8.26 |
▇▆▇▇▃ |
| mean.depth |
HS |
0 |
1 |
-21.56 |
9.8 |
-39.54 |
-27.49 |
-21.12 |
-13.95 |
0.02 |
▅▅▇▆▂ |
Spatial segregation by species
Modelling depth use by species
| -8.037095 |
-29.59214 |
-21.55504 |
-3.873995 |
0.0001957 |
0.7766168 |
| HS |
(Intercept) |
1.2516543 |
0.1038657 |
12.050698 |
0.0000000 |
0.4047722 |
| HS |
mean.depth |
-0.0253018 |
0.0035796 |
-7.068387 |
0.0000000 |
0.4047722 |
| HC |
(Intercept) |
-0.2516543 |
0.1038657 |
-2.422881 |
0.0179507 |
0.4047722 |
| HC |
mean.depth |
0.0253018 |
0.0035796 |
7.068387 |
0.0000000 |
0.4047722 |
After controling for effect of gear type with a mixed effect model. Depth caught still varies significantly with species.
Hence, prefered habitat in terms of depth may vary bewtween H. curtus and H. schistosus
DIfference in diet between H. curtus and H. schsitosus
No. of samples collected by sea snake species
| Hydrophis curtus |
179 |
36 |
18 |
18 |
0.2257251 |
| Hydrophis schistosus |
605 |
93 |
55 |
36 |
0.7629256 |
A very low proportion of inviduals had gut content present at the time of sampling. Sampling accross species and sexes may be adequate for comparison.
Proportion of unidentified specimens
| 26 |
17 |
0.4031008 |
0.2945736 |
A large portion of gut content specimens were unidentifiable. This is an unavoidable consquence of VGCA.
Diverisity of prey families found in gut content
| Hydrophis curtus |
11 |
| Hydrophis schistosus |
20 |
## $Simlarity
## [1] 0.2550017
##
## $StdErr
## [1] 0.14
List of sea snake prey species
| Hydrophis curtus |
|
|
2 |
| Hydrophis curtus |
|
Unidentified |
1 |
| Hydrophis curtus |
Carangidae |
Alepes sp. |
2 |
| Hydrophis curtus |
Carangidae |
Caranx heberi |
2 |
| Hydrophis curtus |
Clupeidae |
Sardinella longiceps |
1 |
| Hydrophis curtus |
Clupeidae |
Sardinella sp. |
2 |
| Hydrophis curtus |
Cynoglossidae |
|
1 |
| Hydrophis curtus |
Cynoglossidae |
Unidentified |
1 |
| Hydrophis curtus |
Engraulidae |
Thryssa dussumieri |
1 |
| Hydrophis curtus |
Engraulidae |
Unidentified |
2 |
| Hydrophis curtus |
Leiognathidae |
Leiognathus sp. |
2 |
| Hydrophis curtus |
Nemipteridae |
Nemepteris sp. |
1 |
| Hydrophis curtus |
Scombridae |
Rastrelliger kanagurta |
2 |
| Hydrophis curtus |
Serranidae |
Epinephelus diacanthus |
1 |
| Hydrophis curtus |
Tetraodontidae |
Lagocephalus inermis |
1 |
| Hydrophis curtus |
Unidentified |
Unidentified |
13 |
| Hydrophis schistosus |
|
|
1 |
| Hydrophis schistosus |
|
Unidentified |
1 |
| Hydrophis schistosus |
Ariidae |
Arius caelatus |
1 |
| Hydrophis schistosus |
Ariidae |
Arius maculatus |
2 |
| Hydrophis schistosus |
Ariidae |
Arius sp. |
3 |
| Hydrophis schistosus |
Ariidae |
Unidentified |
2 |
| Hydrophis schistosus |
Carangidae |
Megalapsis cordyla |
1 |
| Hydrophis schistosus |
Clupeidae |
Sardinella longiceps |
1 |
| Hydrophis schistosus |
Clupeidae |
Sardinella sp. |
3 |
| Hydrophis schistosus |
Clupeidae |
Unidentified |
2 |
| Hydrophis schistosus |
Leiognathidae |
Leiognathus brevirostris |
1 |
| Hydrophis schistosus |
Leiognathidae |
Unidentified |
2 |
| Hydrophis schistosus |
Pleuronectidae |
Unidentified |
1 |
| Hydrophis schistosus |
Plotosidae |
Plotosus lineatus |
4 |
| Hydrophis schistosus |
Plotosidae |
Plotosus sp. |
2 |
| Hydrophis schistosus |
Scombridae |
Rastrelliger kanagurta |
1 |
| Hydrophis schistosus |
Serranidae |
Epinephelus diacanthus |
4 |
| Hydrophis schistosus |
Serranidae |
Epinephelus sp. |
1 |
| Hydrophis schistosus |
Sillaginidae |
Sillago sihama |
1 |
| Hydrophis schistosus |
Synodontidae? |
Unidentified |
2 |
| Hydrophis schistosus |
Teraponidae |
Terapon puta |
2 |
| Hydrophis schistosus |
Teraponidae |
Terapon sp. |
1 |
| Hydrophis schistosus |
Teraponidae |
Terapon theraps |
2 |
| Hydrophis schistosus |
Tetraodontidae |
Arothron sp. |
2 |
| Hydrophis schistosus |
Tetraodontidae |
Chelonodon laticeps |
4 |
| Hydrophis schistosus |
Tetraodontidae |
Lagocephalus inermis |
26 |
| Hydrophis schistosus |
Tetraodontidae |
Unidentified |
1 |
| Hydrophis schistosus |
Unidentified |
Unidentified |
20 |
Relative abundance of prey families in sea snake gut content

Diverisity of prey families found in gut content
| Hydrophis curtus |
10 |
| Hydrophis schistosus |
13 |
| 6.889195 |
0.7849444 |
9.029676 |
0.9356905 |
| Hydrophis curtus |
10 |
9.029676 |
8.344828 |
| Hydrophis schistosus |
13 |
6.889195 |
4.225309 |
Overlap in prey of H. curtus and H. schsitosus
## $Simlarity
## [1] 0.2550017
##
## $StdErr
## [1] 0.1118219
| fam_simboo$Snake.Species |
1 |
1.556349 |
0.0511228 |
3.771403 |
0.002 |
| Residual |
70 |
28.886984 |
0.9488772 |
NA |
NA |
| Total |
71 |
30.443333 |
1.0000000 |
NA |
NA |
Prey preference
| Hydrophis schistosus |
Tetraodontidae |
34.246575 |
38.7307267 |
35.869565 |
2554.804519 |
1 |
| Hydrophis curtus |
Unidentified |
44.827586 |
15.2823920 |
40.625000 |
2506.193436 |
1 |
| Hydrophis schistosus |
Unidentified |
23.287671 |
12.9453244 |
21.739130 |
807.720182 |
2 |
| Hydrophis curtus |
Clupeidae |
6.896552 |
29.9003322 |
9.375000 |
270.864360 |
2 |
| Hydrophis curtus |
Engraulidae |
10.344828 |
11.9601329 |
9.375000 |
220.708271 |
3 |
| Hydrophis curtus |
Carangidae |
13.793103 |
3.3222591 |
12.500000 |
218.238057 |
4 |
| Hydrophis schistosus |
Ariidae |
9.589041 |
8.8407094 |
8.695652 |
168.156891 |
3 |
| Hydrophis schistosus |
Clupeidae |
6.849315 |
10.9456402 |
6.521739 |
119.639584 |
4 |
| Hydrophis schistosus |
Plotosidae |
8.219178 |
7.7882440 |
6.521739 |
117.616299 |
5 |
| Hydrophis curtus |
Scombridae |
6.896552 |
6.6445183 |
6.250000 |
88.927712 |
5 |
| Hydrophis schistosus |
Teraponidae |
6.849315 |
6.5673841 |
5.434783 |
82.206621 |
6 |
| Hydrophis schistosus |
Serranidae |
5.479452 |
7.6303742 |
5.434783 |
71.589900 |
7 |
| Hydrophis curtus |
Cynoglossidae |
6.896552 |
3.9867110 |
6.250000 |
70.598007 |
6 |
| Hydrophis curtus |
Serranidae |
3.448276 |
16.6112957 |
3.125000 |
68.056192 |
7 |
| Hydrophis curtus |
Leiognathidae |
6.896552 |
2.9900332 |
6.250000 |
63.724367 |
8 |
| Hydrophis curtus |
Tetraodontidae |
3.448276 |
7.6411960 |
3.125000 |
37.124814 |
9 |
| Hydrophis schistosus |
Leiognathidae |
4.109589 |
1.0524654 |
3.260870 |
17.726034 |
8 |
| Hydrophis curtus |
Nemipteridae |
3.448276 |
1.6611296 |
3.125000 |
16.503895 |
10 |
| Hydrophis schistosus |
Synodontidae? |
2.739726 |
1.1840236 |
2.173913 |
9.199826 |
9 |
| Hydrophis schistosus |
Sillaginidae |
1.369863 |
2.4206704 |
1.086957 |
4.804968 |
10 |
| Hydrophis schistosus |
Scombridae |
1.369863 |
1.2103352 |
1.086957 |
3.146975 |
11 |
| Hydrophis schistosus |
Pleuronectidae |
1.369863 |
0.3683629 |
1.086957 |
1.993588 |
12 |
| Hydrophis schistosus |
Carangidae |
1.369863 |
0.3157396 |
1.086957 |
1.921502 |
13 |

Selectivity of prey sizes
Variable type: numeric
| Hydrophis curtus |
1 |
0.86 |
2.59 |
0.57 |
2.00 |
2.18 |
2.45 |
2.88 |
3.5 |
| Hydrophis schistosus |
0 |
1.00 |
3.59 |
1.32 |
1.06 |
3.35 |
3.80 |
4.30 |
5.5 |
| -0.6961959 |
2.76775 |
3.463946 |
-2.386272 |
0.0237889 |
0.6420566 |
Difference in resouce use betweek H. curtus and H. schistosus?
Carbon and Nitrogen isotope ratios were compared accorss species. Plasma and scale samples were used to compare short term and long term resource use respectively. Multiples metrics including niche width (SEA), variance (range), overlap (%) were used.
Number of samples analysed
| Hydrophis curtus |
6 |
12 |
| Hydrophis schistosus |
27 |
25 |
Summary statistics on Carbon and Nitrogen stable isotopes
| Hydrophis curtus |
Plasma |
-17.6±0.6 |
13.23±0.56 |
| Hydrophis curtus |
Scales |
-15.44±0.59 |
14.57±1.26 |
| Hydrophis schistosus |
Plasma |
-16.72±1.14 |
14.45±1.12 |
| Hydrophis schistosus |
Scales |
-14.95±1.25 |
15.13±1.14 |
Difference in niche width between sea snakes
Maximum likelihood estimate of SEA
| Hydrophis curtus.Plasma |
0.74470 |
0.6368364 |
0.8491152 |
| Hydrophis curtus.Scales |
4.58370 |
2.4210563 |
2.7236883 |
| Hydrophis schistosus.Plasma |
10.19485 |
3.1208774 |
3.2851342 |
| Hydrophis schistosus.Scales |
20.43275 |
4.4823982 |
4.7065181 |
As maximum likelihood can only porivde point estimates of SEA, a bayesian model was used to provide more robust comparison of niche width.
Bayesian estimate of SEA
| Hydrophis curtus |
Plasma |
1.107423 |
0.6453675 |
0.0102042 |
| Hydrophis curtus |
Scales |
4.698527 |
1.0578248 |
0.0167257 |
| Hydrophis schistosus |
Plasma |
2.720573 |
0.9673557 |
0.0152952 |
| Hydrophis schistosus |
Scales |
3.304453 |
0.7527456 |
0.0119020 |
Testing difference in species niche area by tissue type
| Plasma |
0.94925 |
| Scales |
0.13025 |
Hyp: H. schistosus SEA is larger than H. curtus
While niche width is slightly larger in H. schistosus, it is not significantly different. The posterior distribution of SEA^b has right skewed long tail (masked by the limits of the graph for visual clarity) possibly due to the low sample size. Niche width doesn’t seem to change accross different tissue types either, indicating stability over variying periods of assimilation.
Visualising posterior ellipses to compare species isotopic niche

As seen in the SEA estimation, low sample size for H. curtus causes greater uncertainty in the estimation of standar ellipses even with bayesian inference. Both carbon and nitrogen isotpes seem to be enriched in scales when compared to plasma. Degree of overlap appears to be low for both tissues.
- Samples sizes for H. curtus in both tissues need to be increased despite using bayesian methods
- Unusual outlier in H. schistosus scales data needs to be checked
Relative overlap in bayesian standard ellipses

| Long-term |
0.4244165 |
0.0827186 |
| Short-term |
0.0846205 |
0.0734810 |
Overlap between H. curtus and H. schistosus seems to be high in when comparing long term resource use, i.e., scales.
However, overlap between H. curtus and H. schistosus seems to be very low when comparing short term resource use, i.e., plasma.
This difference could be caused by:
- low sample size for H. curtus
- differences in processing of scales and plasma, i.e., lipid extraction
Does fishing intensity affect the distribution of H. curtus and H. schistosus?
Spatial overlap between fisheries and sea snakes
| GillNet |
HC |
30 |
49 |
0.6122449 |
| GillNet |
HS |
39 |
51 |
0.7647059 |
| Trawler |
HC |
47 |
49 |
0.9591837 |
| Trawler |
HS |
46 |
51 |
0.9019608 |
## Error in (function (classes, fdef, mtable) : unable to find an inherited method for function 'select' for signature '"grouped_df"'
Variation in relative proportion of HC with fishing intensity
| (Intercept) |
-0.2644395 |
0.1108086 |
-2.3864521 |
0.0197591 |
| GillNet |
0.0030194 |
0.0062982 |
0.4794069 |
0.6331652 |
| Trawler |
-0.0004375 |
0.0012801 |
-0.3417601 |
0.7335702 |
| mean.depth |
-0.0258173 |
0.0037580 |
-6.8699998 |
0.0000000 |
| GillNet |
0.0306342 |
1 |
0.2298310 |
0.6331652 |
| Trawler |
0.0155683 |
1 |
0.1167999 |
0.7335702 |
| mean.depth |
6.2908730 |
1 |
47.1968975 |
0.0000000 |
| Residuals |
9.1970078 |
69 |
NA |
NA |

Overlap between fisheries catch and sea snake diet
Sampling Adequacy
| Gill Net |
38 |
35.41667 |
| Trawler |
140 |
434.65000 |
Catch weight
##
## Shapiro-Wilk normality test
##
## data: log(tonnage$Total.Catch..kg.)
## W = 0.96656, p-value = 0.02034
| -0.8347031 |
4.585903 |
5.420606 |
-3.896286 |
0.0002104 |
75.08903 |
-1.261464 |
-0.4079425 |
Welch Two Sample t-test |
two.sided |
## [1] 0.8447173
Diverisity of prey families found in fisheries catch
No. of Sea snake prey families found in fish catch and overlap
| Gill Net |
HC |
7 |
| Gill Net |
HS |
6 |
| Trawler |
HC |
9 |
| Trawler |
HS |
9 |
| Gill Net |
HC |
0.8204191 |
| Gill Net |
HS |
0.7958067 |
| Trawler |
HC |
0.7356892 |
| Trawler |
HS |
0.4831901 |
| Gill Net |
0.0246124 |
0.8204191 |
0.7958067 |
0.6314888 |
0.5296802 |
0.1448735 |
| Trawler |
0.2524990 |
0.7356892 |
0.4831901 |
7.0551602 |
0.0000000 |
0.8924545 |
| HC |
0.0847299 |
0.8204191 |
0.7356892 |
2.469163 |
0.0153629 |
0.3588295 |
| HS |
0.3126166 |
0.7958067 |
0.4831901 |
7.761277 |
0.0000000 |
1.0913295 |
Sea snake prey species in fisheries catch
Species constituting >10% of the catch on average are represented

Does isotopic niche of sea snakes change with local fishing intensity?
As it is infeasible to to find sites with little to no fishing pressure on mainland India. The ultimate objective of this project remains unfulfilled it is nigh impossible to conduct a study with controls and test sites with varying levels of fishing pressure.
How do you test the niche shift hypotheses with out spatial replicates?
While the control - test study design failed, fishing effort data was collected from multiple vessels (Gillnet and Trawlers) landing at the Malvan harbour over the period of 1.5 years along side diet, abundance (snakes and prey), and isotopic data. So we ask the following questions:
- Is there a corellation between fishing intensity and isotopic ratios?
- Do niche metrics (width, overlap) vary with fishing pressure (high, medium and low preiods during the year)?
What temporal resolution should be used for the analysis?
- Day, week, month or season.
Which is appropriate and why?
Depending on the tissue being analysed. Scales - month, Plasma - week
What are the existing data and sampling structures and what can be improved?

#Stable isotope data
sia = read.csv("../Data/Stable Isotope Data_CEAS_241119.csv")
#joining sia data to snake data
sia_snakes = sia%>%
filter(Tissue.type != "Gut Content")%>%
left_join(snakes, 'Field.Code')%>%
mutate(Lab = "CEAS")%>%
rename(Delta.Carbon = d13C..vpdb. , Delta.Nitrogen = d15N..N2.air.)%>%
dplyr::select(Date, Field.Code, Species, Snout.to.Vent..cm., Sex, Gravid, Class,
Gear.Type, Fishing.Location, Depth.Caught..m.,
Plasma.Color, Delta.Carbon, Delta.Nitrogen, Lab,
Tissue.type, Month, Year)
sia_li <- sia_fi%>%
group_by(Field.Code, Species, Tissue.type, Delta.Carbon, Delta.Nitrogen)%>%
nest()%>%
mutate(cell = map(data, cell.ext),
celldf = map(cell, as.data.frame))%>%
dplyr::select(celldf)%>%
unnest()%>%
inner_join(fi, by = c("x", "y"))
write.csv(sia_li, "./Data/SIA_fishing intensity.csv")
Sample size
##
## Plasma Scales
## Hydrophis schistosus 11 12
Variation Carbon isotope ratio with fishing intensity

Modeling isotope ratios with fishing intensity
Continous model
| Hydrophis schistosus |
Delta.Carbon |
(Intercept) |
-15.4011808 |
0.6232436 |
-24.711336 |
0.0000000 |
0.1925198 |
| Hydrophis schistosus |
Delta.Carbon |
intensity |
-0.0119892 |
0.0065172 |
-1.839621 |
0.0989712 |
0.1925198 |
| Hydrophis schistosus |
Delta.Nitrogen |
(Intercept) |
15.7569605 |
0.3712895 |
42.438473 |
0.0000000 |
0.2023267 |
| Hydrophis schistosus |
Delta.Nitrogen |
intensity |
-0.0073013 |
0.0038825 |
-1.880548 |
0.0927251 |
0.2023267 |
Samples sizes for H. curtus are low, however, fishing intensity seems to have a significant depletion effect on plasma isotope ratios in H. schistosus.
Difference in niche width between sea snakes
Maximum likelihood estimate of SEA
| Hydrophis schistosus.Low |
2.1424 |
1.234995 |
1.440828 |
| Hydrophis schistosus.High |
1.2033 |
2.182545 |
4.365089 |
As maximum likelihood can only porivde point estimates of SEA, a bayesian model was used to provide more robust comparison of niche width.
Bayesian estimate of SEA
| Hydrophis schistosus |
High |
3.468871 |
3.1500851 |
0.0498072 |
| Hydrophis schistosus |
Low |
1.529057 |
0.6105229 |
0.0096532 |
Testing difference in species niche area by tissue type
| Hydrophis schistosus |
0.82375 |
